Virtual Assistant Host Platform Configured for Interactive Voice Response Simulation

ABSTRACT

Aspects of the disclosure relate to using machine learning to simulate an interactive voice response system. A computing platform may establish a virtual assistant session with a mobile banking application executing on a mobile device, which may include authenticating at least one authentication credential associated with an online banking account. The computing platform may receive an assistance message from the mobile device requesting assistance. Using a machine learning model, the computing platform may identify an intent of the assistance message. The computing platform may generate a response message based on the intent of the assistance message. The computing platform may send the response message and one or more commands directing the mobile device to output an audio response file based on the response message to the mobile device, which may cause the mobile device to convert the response message into the audio response file and output the audio response file.

BACKGROUND

Aspects of the disclosure relate to interactive voice response (IVR)sessions. In particular, one or more aspects of the disclosure relate tocomputing platforms that implement machine learning algorithms anddatasets to enable interactive voice response sessions.

In some cases, IVR systems may connect a customer request to arespective call center agent through a series of decisions. In someinstances, however, this may consume considerable time for bothcustomers and agents, and/or may result in processing delays.Furthermore, such processing of customer requests may overload certaincomputing resources while underutilizing others. Accordingly, it may bedifficult for enterprise organizations to achieve the benefits of IVRsystems while avoiding the corresponding delays and processinginefficiencies.

SUMMARY

Aspects of the disclosure provide effective, efficient, scalable, andconvenient technical solutions that address and overcome the technicalproblems associated with interactive voice response (IVR) systems. Forexample, some aspects of the disclosure provide techniques that mayenable computing devices to train a machine learning model usingpreviously recorded phone and virtual IVR sessions, use the model toidentify user intents, and provide automated responses accordingly. Indoing so, various technical advantages may be realized. For example, onetechnical advantage is that enterprise computing and human resources maybe conserved by routing client requests to an artificial intelligenceengine rather than contact center resources, agents, or the like.Furthermore, another technical advantage is that processing load may bedynamically balanced by the artificial intelligence engine rather thanexhausting certain resources and/or underutilizing others, which maylead to processing delays. Accordingly, these advantages may result inincreased enterprise capabilities, such as providing automated voiceresponses to client questions, while reducing processing load onenterprise resources.

In accordance with one or more embodiments of the disclosure, acomputing platform comprising at least one processor, a communicationinterface, and memory storing computer-readable instructions mayestablish a virtual assistant session with a mobile banking applicationexecuting on a mobile device, which may include authenticating at leastone authentication credential associated with an online banking account.The computing platform may receive an assistance message from the mobiledevice requesting assistance. Using a machine learning model, thecomputing platform may identify an intent of the assistance message. Thecomputing platform may generate a response message based on the intentof the assistance message. The computing platform may send the responsemessage and one or more commands directing the mobile device to outputan audio response file based on the response message to the mobiledevice, which may cause the mobile device to convert the responsemessage into the audio response file and output the audio response file.

In one or more instances, the computing platform may authenticate the atleast one authentication credential associated with the online bankingaccount by authenticating one or more of: a user name, a password,biometric information, or a voice input. In one or more instances, priorto identifying the intent, the computing platform may train the machinelearning model based on a plurality of recorded interactive voiceresponse (IVR) sessions, where the plurality of recorded interactivevoice response sessions include one or more of: phone sessions orvirtual IVR sessions with one or more online banking customers.

In one or more instances, the computing platform may identify the intentby identifying one or more of: a balance inquiry request, a transactionstatus request, a request for information corresponding to a failedtransaction, a credit score inquiry, credit card information,charge/payment information, a request for account information, amortgage request, a request to execute a transaction, or a request foroutage information. In one or more instances, the computing platform maygenerate the response message based on the intent of the assistancemessage by: 1) sending one or more commands directing an eventprocessing system to process an event based on the intent of theassistance message, where sending the one or more commands directing theevent processing system to process the event based on the intent of theassistance message causes the event processing system to process theevent; 2) receiving, from the event processing system, an eventprocessing notification indicating that the event was processed; and 3)generating, based on the event processing notification indicating thatthe event was processed, the assistance message.

In one or more instances, the computing platform may identify the intentof the assistance message based at least in part on information from themobile device. In one or more instances, the virtual assistant sessionmay correspond to a data channel between the mobile device and anartificial intelligence engine hosted by the computing platform.

In accordance with one or more additional or alternative embodiments ofthe disclosure, a computing platform comprising at least one processor,a communication interface, and memory storing computer-readableinstructions may receive user interaction information corresponding tointeractions between a user and one or more enterprise computingdevices. The computing platform may establish a virtual assistantsession with a mobile device. Based on the user interaction informationcorresponding to the interactions between the user and the one or moreenterprise computing devices, the computing platform may identify one ormore predicted intents for the user. The computing platform may generatehotkey information based on the one or more predicted intents for theuser. The computing platform may send the hotkey information and one ormore commands directing the mobile device to output the hotkeyinformation to the mobile device, which may cause the mobile device tooutput the hotkey information. The computing platform may receive hotkeyinput information from the mobile device. Based on the hotkey inputinformation, the computing platform may generate a hotkey responsemessage. The computing platform may send, to the mobile device, thehotkey response message and one or more commands directing the mobiledevice to convert the hotkey response message to an audio output and tooutput the audio output, which may cause the mobile device to convertthe hotkey response message to the audio output and to output the audiooutput.

In one or more instances, in sending the hotkey information and the oneor more commands directing the mobile device to output the hotkeyinformation to the mobile device, the computing platform may cause themobile device to convert the hotkey information to a hotkey audio outputand to output the hotkey audio output. In one or more instances, thehotkey audio output may indicate that one or more numeric valuesdisplayed on a display of the mobile device correspond to one or moreof: a balance inquiry request, a transaction status request, a requestfor information corresponding to a failed transaction, a credit scoreinquiry, credit card information, charge/payment information, a requestfor account information, a mortgage request, a request to execute atransaction, or a request for outage information.

In one or more instances, the one or more enterprise computing devicesmay include one or more of: an automated teller machine (ATM) or acomputing device at a branch location of a financial institution. In oneor more instances, establishing the virtual assistant session with themobile device may include establishing the virtual assistant sessionwith a mobile banking application executing on the mobile device, andestablishing the virtual assistant session with the mobile bankingapplication executing on the mobile device may include authenticating atleast one authentication credential associated with an online bankingaccount.

In one or more instances, authenticating the at least one authenticationcredential associated with the online banking account may includeauthenticating one or more of: a user name, a password, biometricinformation, or a voice input. In one or more instances, the computingplatform may receive second user interaction information correspondingto interactions between the user and the one or more enterprisecomputing devices. The computing platform may establish a second virtualassistant session with the mobile device. Based on the user interactioninformation corresponding to the interactions between the user and theone or more enterprise computing devices, the computing platform mayidentify one or more second predicted intents for the user. Thecomputing platform may generate second hotkey information based on theone or more second predicted intents for the user, where the secondhotkey information is different than the hotkey information.

In one or more instances, the computing platform may receive second userinteraction information corresponding to interactions between a seconduser and one or more second enterprise computing devices. The computingplatform may establish a second virtual assistant session with themobile device. Based on the second user interaction informationcorresponding to the interactions between the second user and the one ormore second enterprise computing devices, the computing platform mayidentify one or more predicted intents for the second user. Thecomputing platform may generate second hotkey information based on theone or more predicted intents for the second user, where the secondhotkey information is different than the hotkey information.

In one or more instances, the computing platform may identify the one ormore predicted intents for the user by identifying, using a machinelearning model, the one or more predicted intents for the user, wherethe machine learning model is trained, prior to identifying the one ormore predicted intents, based on a plurality of recorded interactivevoice response (IVR) sessions, where the plurality of recordedinteractive voice response sessions correspond to one or more of: phonesessions or virtual IVR sessions with one or more online bankingcustomers. In one or more instances, the computing platform may send oneor more commands directing an event processing system to process anevent based on the hotkey input information, which may cause the eventprocessing system to process the event. The computing platform mayreceive, from the event processing system, an event processingnotification indicating that the event was processed. Based on the eventprocessing notification indicating that the event was processed, thecomputing platform may generate the hotkey response message.

These features, along with many others, are discussed in greater detailbelow.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is illustrated by way of example and not limitedin the accompanying figures in which like reference numerals indicatesimilar elements and in which:

FIGS. 1A-1B depict an illustrative computing environment forimplementing machine learning to enable IVR simulation in accordancewith one or more example embodiments;

FIGS. 2A-2H depict an illustrative event sequence for implementingmachine learning to enable IVR simulation in accordance with one or moreexample embodiments; and

FIGS. 3 and 4 depict illustrative methods for implementing machinelearning to enable IVR simulation in accordance with one or more exampleembodiments.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown, by way of illustration, variousembodiments in which aspects of the disclosure may be practiced. In someinstances, other embodiments may be utilized, and structural andfunctional modifications may be made, without departing from the scopeof the present disclosure.

It is noted that various connections between elements are discussed inthe following description. It is noted that these connections aregeneral and, unless specified otherwise, may be direct or indirect,wired or wireless, and that the specification is not intended to belimiting in this respect.

As a brief introduction to the concepts described further herein, one ormore aspects of the disclosure describe a virtual assistant system thatmay be developed and deployed to provide customers with access to asimulated interactive voice response (IVR) service. Specifically, avoice assistant for IVR with context based responses is describedherein. The assistant may understand the context of a customer's call tothe IVR, and may return a response to the customer accordingly. In someinstances, the virtual assistant may directly speak to the customer witha voice response, understand user utterances, and/or allow the customerto continue a conversation with the virtual assistant. Additionally oralternatively, the virtual assistant may provide the ability forcustomers to use hot keys within an IVR dialer for contextual response,frequently asked questions, or the like, and may subsequently hand offthese requests to a conversation window, live agent, or the like forother intents.

Many IVR systems operate by connecting customer requests to a respectivecontact center agent through a series of option flows, which may consumesubstantial time from the customer and substantial contact centerresources. In many scenarios, the context of these customer requests aresimple (e.g., relating account information, credit card statement, lastfailed transaction, or the like). Accordingly, if the IVR can be madeintelligent with voice based virtual assistant functionality with adialer directly on a mobile application, contact center resources may beconserved and customer experience may be improved. In short, rather thanbeing serviced by a live agent, the customer may be serviced by anartificial intelligence (AI)-enabled assistant.

FIGS. 1A-1B depict an illustrative computing environment that implementsmachine learning to enable IVR simulation in accordance with one or moreexample embodiments. Referring to FIG. 1A, computing environment 100 mayinclude one or more computer systems. For example, computing environment100 may include a mobile device 102, virtual assistant host platform103, enterprise computing device 104, and event processing system 105.

Mobile device 102 may be a mobile device, tablet, smartphone, or thelike that may be used by an individual such as a customer of anenterprise organization (e.g., a financial institution). For example,the mobile device 102 may be used to interact with an account for anenterprise organization (e.g., an online banking account, or the like).In some instances, the mobile device 102 may be configured tocommunicate with a virtual assistant host platform (e.g., virtualassistant host platform 103, or the like) to provide one or more virtualassistant services to the individual. In some instances, mobile device102 may be configured to display one or more user interfaces (e.g.,online banking interfaces, or the like) and/or provide one or more audiooutputs.

As described further below, virtual assistant host platform 103 may be acomputer system that includes one or more computing devices (e.g.,servers, server blades, or the like) and/or other computer components(e.g., processors, memories, communication interfaces) that may be usedto host and maintain an IVR simulation model. In some instances, thevirtual assistant host platform 103 may be configured to train the IVRsimulation model using previously recorded phone calls and/or IVRsessions, use the IVR simulation model to identify an intent of anindividual, and to provide automated responses to the individual and/orcause one or more events to be processed based on the intent. In someinstances, the virtual assistant host platform 103 may be configured todynamically update the IVR simulation model as additional data and/orfeedback is received.

Enterprise computing device 104 may be one or more computing devicessuch as automated teller machines (ATM), teller computing devices, orthe like. For example, the enterprise computing device 104 may be usedto receive user interaction inputs, which may, in some instances, causethe enterprise computing device 104 to perform one or more tasks basedon the user interaction input (e.g., deposit, withdrawal, check balance,or the like). In some instances, the enterprise computing device 104 maybe configured to communicate with the virtual assistant host platform103 to provide user interaction information.

Event processing system 105 may be a server, server blade, or the likeconfigured to perform one or more enterprise activities (e.g., onlinebanking activities, financial transactions, trades, or the like). Insome instances, the event processing system 105 may correspond to one ormore backend resources corresponding to an enterprise organization. Forexample, event processing system 105 may be maintained by an enterpriseorganization, such as a financial institution.

Computing environment 100 also may include one or more networks, whichmay interconnect mobile device 102, virtual assistant host platform 103,enterprise computing device 104, event processing system 105, or thelike. For example, computing environment 100 may include a network 101(which may interconnect, e.g., mobile device 102, virtual assistant hostplatform 103, enterprise computing device 104, event processing system105, or the like).

In one or more arrangements, mobile device 102, virtual assistant hostplatform 103, enterprise computing device 104, and/or event processingsystem 105 may be any type of computing device capable of sending and/orreceiving requests and processing the requests accordingly. For example,mobile device 102, virtual assistant host platform 103, enterprisecomputing device 104, event processing system 105, and/or the othersystems included in computing environment 100 may, in some instances, beand/or include server computers, desktop computers, laptop computers,tablet computers, smart phones, or the like that may include one or moreprocessors, memories, communication interfaces, storage devices, and/orother components. As noted above, and as illustrated in greater detailbelow, any and/or all of mobile device 102, virtual assistant hostplatform 103, enterprise computing device 104, and/or event processingsystem 105, may, in some instances, be special-purpose computing devicesconfigured to perform specific functions.

Referring to FIG. 1B, virtual assistant host platform 103 may includeone or more processors 111, memory 112, and communication interface 113.A data bus may interconnect processor 111, memory 112, and communicationinterface 113. Communication interface 113 may be a network interfaceconfigured to support communication between virtual assistant hostplatform 103 and one or more networks (e.g., network 101, or the like).Memory 112 may include one or more program modules having instructionsthat when executed by processor 111 cause virtual assistant hostplatform 103 to perform one or more functions described herein and/orone or more databases that may store and/or otherwise maintaininformation which may be used by such program modules and/or processor111. In some instances, the one or more program modules and/or databasesmay be stored by and/or maintained in different memory units of virtualassistant host platform 103 and/or by different computing devices thatmay form and/or otherwise make up virtual assistant host platform 103.For example, memory 112 may have, host, store, and/or include virtualassistant host module 112 a, virtual assistant host database 112 b, anda machine learning engine 112 c.

Virtual assistant host module 112 a may have instructions that directand/or cause virtual assistant host platform 103 to execute advancedmachine learning techniques to provide one or more virtual assistservices, such as simulated IVR, as discussed in greater detail below.Virtual assistant host database 112 b may store information used byvirtual assistant host module 112 a and/or virtual assistant hostplatform 103 in application of advanced machine learning techniques toprovide one or more virtual assist services, and/or in performing otherfunctions. Machine learning engine 112 c may have instructions thatdirect and/or cause the virtual assistant host platform 103 to set,define, and/or iteratively refine optimization rules and/or otherparameters used by the virtual assistant host platform 103 and/or othersystems in computing environment 100.

FIGS. 2A-2H depict an illustrative event sequence that implementsmachine learning to enable IVR simulation in accordance with one or moreexample embodiments. Referring to FIG. 2A, at step 201, the mobiledevice 102 may establish a connection with the virtual assistant hostplatform 103. For example, the mobile device 102 may establish a firstwireless data connection with the virtual assistant host platform 103 tolink the mobile device 102 to the virtual assistant host platform 103(e.g., in preparation for initiating a virtual assistance session). Insome instances, the mobile device 102 may identify whether or not aconnection is already established with the virtual assistant hostplatform 103. If a connection is already established with the virtualassistant host platform 103, the mobile device 102 might notre-establish the connection. If a connection is not yet established withthe virtual assistant host platform 103, the mobile device 102 mayestablish the first wireless data connection as described herein.

At step 202, the mobile device 102 may initiate a virtual assistancesession with the virtual assistant host platform 103. For example, themobile device 102 may establish a virtual assistance session between anapplication running on the mobile device 102 (e.g., a mobile bankingapplication, or the like) and the virtual assistant host platform 103(e.g., an artificial intelligence engine running at the virtualassistant host platform 103). In some instances, in establishing thevirtual assistance session, the mobile device 102 may establish asession with the virtual assistant host platform 103 that enables a userof the mobile device 102 to provide a voice input, and receive an audiooutput in response (which may e.g., be generated using a machinelearning model hosted by the virtual assistant host platform 103). Insome instances, in initiating the virtual assistance session, the mobiledevice 102 and/or the virtual assistant host platform 103 mayauthenticate the mobile device 102 and/or the user of the mobile device102 (e.g., based on a user name, a password, biometric information, avoice input, or the like, which may, in some instances, be associatedwith an online banking account).

At step 203, the mobile device 102 may receive an assistance input. Forexample, the mobile device 102 may receive a voice input from the userof the mobile device 102 requesting a response to an inquiry, an eventto be processed, or the like.

In some instances, the mobile device 102 may receive a user inputindicating a particular inquiry to be made, event to be processed, orthe like. In other instances, the mobile device 102 may receive a userinput requesting to speak with a live representative. In theseinstances, the mobile device 102 may contact a call center and cause avoice call session to be established between the mobile device 102 and acomputing device operated by an employee of the enterprise organization(e.g., a customer service representative at a call center for afinancial institution). In operating in this manner, the mobile device102 and the virtual assistant host platform 103 may reduce load onrepresentatives and/or computing resources at the call center byautomatically handling a large percentage of requests through theautomated IVR process, as described further below. Similarly, this mayreduce customer delays (e.g., the user does not need to wait for a liverepresentative, or, if he or she does need a live representative, due tothe reduced load, wait times may be reduced or eliminated).

At step 204, the mobile device 102 may convert the assistance inputreceived at step 203 into an assistance message (e.g., convert fromaudio to text). For example, the mobile device 102 may apply one or morenatural language processing techniques to convert the assistance inputfrom an audio file into a text file, which may, e.g., be sent as amessage to the virtual assistant host platform 103 for processing.

Referring to FIG. 2B, at step 205, the mobile device 102 may send theassistance message to the virtual assistant host platform 103. Forexample, the mobile device 102 may send the assistance message to thevirtual assistant host platform 103 while the first wireless dataconnection is established.

At step 206, the virtual assistant host platform 103 may receive theassistance message sent at step 205. For example, the virtual assistanthost platform 103 may receive the assistance message via thecommunication interface 113 and while the first wireless data connectionis established.

At step 207, the virtual assistant host platform 103 may identify anintent from the assistance message. For example, the virtual assistanthost platform 103 may input the assistance message into an IVRsimulation model hosted by the virtual assistant host platform 103. Forexample, the virtual assistant host platform 103 may train the IVRsimulation model based on previously recorded audio files correspondingto phone call and/or virtual IVR sessions with one or more individuals(e.g., online banking customers, or the like). In doing so, the virtualassistant host platform 103 may label data corresponding to theseprevious phone and/or virtual IVR sessions with an identified intent.Then, to identify the intent from the assistance message, the virtualassistant host platform 103 may identify data stored in the IVRsimulation model that corresponds to the assistance message, and mayidentify an intent corresponding to the identified data. For example, inidentifying the intent from the assistance message, the virtualassistant host platform 103 may identify one or more of: a balanceinquiry request, a transaction status request, a request for informationcorresponding to a failed transaction, a credit score inquiry, creditcard information, charge/payment information, a request for accountinformation, a mortgage request, a request to execute a transaction, arequest for outage information, a request to process a transaction, arequest to initiate a fund transfer, or the like.

In some instances, the virtual assistant host platform 103 may identifywhether or not it has locally stored information that may be used tosatisfy the intent or is otherwise configured to satisfy the intentwithout assistance from the event processing system 105. If the virtualassistant host platform 103 is configured to satisfy the intent usinglocal resources, the virtual assistant host platform 103 may proceed tostep 214. If the virtual assistant host platform 103 is not configuredto satisfy the intent using local resources, the virtual assistant hostplatform 103 may proceed to step 208.

At step 208, the virtual assistant host platform 103 may establish aconnection with event processing system 105. For example, the virtualassistant host platform 103 may establish a second wireless dataconnection with the event processing system 105 to link the virtualassistant host platform 103 to the event processing system 105 (e.g., inpreparation for sending one or more commands directing the eventprocessing system 105 to process an event, provide information, the likebased on the identified assistance message intent). In some instances,the virtual assistant host platform 103 may identify whether or not aconnection is already established with the event processing system 105.If a connection is already established with the event processing system105, the virtual assistant host platform 103 might not re-establish theconnection. If a connection is not yet established with the eventprocessing system 105, the virtual assistant host platform 103 mayestablish the second wireless data connection as described herein.

At step 209, the virtual assistant host platform 103 may send one ormore event processing commands to the event processing system 105. Forexample, the virtual assistant host platform 103 may send the one ormore event processing commands to the event processing system 105 viathe communication interface 113 and while the second wireless dataconnection is established.

At step 210, the event processing system 105 may receive the one or moreevent processing commands sent at step 209. For example, the eventprocessing system 105 may receive the one or more event processingcommands while the second wireless data connection is established.

Referring to FIG. 2C, at step 211, the event processing system 105 mayprocess an event, provide a response to an inquiry, or the like based onor in response to the one or more event processing commands received atstep 210. For example, the event processing system 105 may identify anaccount balance, a transaction status, failed transaction information,credit score information, credit card information, charge/paymentinformation, account information, mortgage information, outageinformation, or the like. Additionally or alternatively, the eventprocessing system 105 may process or otherwise execute a transaction,fund transfer, or the like.

At step 212, the event processing system 105 may generate and send anevent processing notification based on the event and/or inquiryprocessed at step 211. For example, the event processing system 105 maygenerate a notification indicating an account balance, a transactionstatus, failed transaction information, credit score information, creditcard information, charge/payment information, account information,mortgage information, outage information, or the like. Additionally oralternatively, the event processing system 105 may generate anotification indicating that a transaction, fund transfer, or the likewas executed. In some instances, the event processing system 105 maysend the event processing notification to the virtual assistant hostplatform 103 while the second wireless data connection is established.

At step 213, the virtual assistant host platform 103 may receive theevent processing notification sent at step 212. For example, the virtualassistant host platform 103 may receive the event processingnotification via the communication interface 113 and while the secondwireless data connection is established.

At step 214, the virtual assistant host platform 103 may generate aresponse message based on the event processing notification received atstep 213. For example, the virtual assistant host platform 103 maygenerate the response message based on the information included in theevent processing notification. In some instances, in addition to theresponse message, the virtual assistant host platform 103 may generateone or more commands directing the mobile device 102 to convert theresponse message from text to audio, and to output the converted audioresponse message.

At step 215, the virtual assistant host platform 103 may send theresponse message and/or the one or more commands directing the mobiledevice 102 to convert the response message from text to audio, and tooutput the converted audio response message to the mobile device 102.For example, the virtual assistant host platform 103 may send theresponse message and/or the one or more commands directing the mobiledevice 102 to convert the response message from text to audio, and tooutput the converted audio response message via the communicationinterface 113 and while the first wireless data connection isestablished.

At step 216, the mobile device 102 may receive the response messageand/or the one or more commands directing the mobile device 102 toconvert the response message from text to audio, and to output theconverted audio response message to the mobile device 102 sent at step215. For example, the mobile device 102 may receive the response messageand/or the one or more commands directing the mobile device 102 toconvert the response message from text to audio, and to output theconverted audio response message via the communication interface 113 andwhile the first wireless data connection is established.

Referring to FIG. 2D, at step 217, the mobile device 102 may convert theresponse message to an audio response output. For example, the mobiledevice 102 may use one or more text to speech techniques to convert theresponse message (e.g., which may be in text form) to an audio responseoutput. In some instances, the mobile device 102 may convert theresponse message to an audio response output based on or in response tothe one or more commands directing the mobile device 102 to convert theresponse message from text to audio, and to output the converted audioresponse message.

At step 218, the mobile device 102 may output the audio response outputgenerated at step 217. For example, the mobile device 102 may output theaudio response output based on or in response to the one or morecommands directing the mobile device 102 to convert the response messagefrom text to audio, and to output the converted audio response message.For example, the mobile device 102 may cause an audio output of anaccount balance, a transaction status, failed transaction information,credit score information, credit card information, charge/paymentinformation, account information, mortgage information, outageinformation, a transaction status, or the like as a response to theassistance message sent at step 205. In some instances, the mobiledevice 102 may receive feedback corresponding to the audio responseoutput (e.g., did it satisfy the user intent, or the like), and may sendthe feedback to the virtual assistant host platform 103, which mayupdate the IVR simulation model accordingly.

Steps 219-248, as described below, describe an additional or alternativeembodiment to that described above with regard to steps 201-218. In someinstances, steps 201-218 and/or steps 219-248 may be performedindependently of each other. In other instances, steps 201-218 and steps219-248 may both be performed (e.g., simultaneously, sequentially, orthe like).

At step 219, enterprise computing device 104 may receive a userinteraction input. For example, the enterprise computing device 104 mayreceive a user interaction input corresponding to an ATM transaction,branch transaction, online transaction, or the like performed by theuser of the mobile device 102.

At step 220, the enterprise computing device 104 may establish aconnection with the virtual assistant host platform 103. For example,the enterprise computing device 104 may establish a third wireless dataconnection with the virtual assistant host platform 103 to link theenterprise computing device 104 to the virtual assistant host platform103 (e.g., in preparation for sending user interaction information). Insome instances, the enterprise computing device 104 may identify whetheror not a connection is already established with the virtual assistanthost platform 103. If a connection is already established with thevirtual assistant host platform 103, the enterprise computing device 104might not re-establish the connection. If a connection is not yetestablished with the virtual assistant host platform 103, the enterprisecomputing device 104 may establish the third wireless data connection asdescribed herein.

Referring to FIG. 2E, at step 221, the enterprise computing device 104may send user interaction data to the virtual assistant host platform103. For example, the enterprise computing device 104 may send datacorresponding to the user interaction input received at step 219. Insome instances, the enterprise computing device 104 may send the userinteraction data to the virtual assistant host platform 103 while thethird wireless data connection is established.

At step 222, the virtual assistant host platform 103 may receive theuser interaction data sent at step 221. For example, the virtualassistant host platform 103 may receive the user interaction data viathe communication interface 113 and while the third wireless dataconnection is established. In some instances, the virtual assistant hostplatform 103 may store the user interaction data in the IVR simulationmodel along with one or more user identifiers that may be used toidentify user interaction data corresponding to the user.

In some instances, the user may interact with a plurality of enterprisecomputing devices similar to enterprise computing device 104, and steps219-222 may be repeated for each enterprise computing device (e.g., toestablish a machine learning database corresponding to recent activitiesperformed by the user at enterprise computing devices). Additionally oralternatively, steps 219-222 may be repeated for interactions betweenvarious other customers and a plurality of enterprise computing devices(e.g., to establish a machine learning database of frequentinteractions, general outages, or the like that may apply to a pluralityof customers that includes the user of the mobile device 102).

At step 223, the mobile device 102 may initiate a virtual assistancesession with the virtual assistant host platform 103. For example, themobile device 102 may establish a virtual assistance session between anapplication running on the mobile device 102 (e.g., a mobile bankingapplication, or the like) and the virtual assistant host platform 103.In some instances, in establishing the virtual assistance session, themobile device 102 may establish a session with the virtual assistanthost platform 103 that enables a user of the mobile device 102 toprovide a voice input, and receive an audio output in response (whichmay e.g., be generated using a machine learning model hosted by thevirtual assistant host platform 103). In some instances, in initiatingthe virtual assistance session, the mobile device 102 and/or the virtualassistant host platform 103 may authenticate the mobile device 102and/or the user of the mobile device 102 (e.g., based on a user name, apassword, biometric information, a voice input, or the like, which may,in some instances, be associated with an online banking account). Insome instances, actions performed at step 223 may be similar to thosedescribed above with regard to step 202.

At step 224, the virtual assistant host platform 103 may identify theuser of the mobile device 102. For example, the virtual assistant hostplatform 103 may identify the user based on authentication information,a device identifier, or the like sent at step 223 to initiate thevirtual assistant session. Additionally or alternatively, the virtualassistant host platform 103 may apply one or more voice recognitiontechniques to identify the user based on his or her voice.

At step 225, the virtual assistant host platform 103 may generate hotkeyinformation for the identified user. For example, the virtual assistanthost platform 103 may use the IVR simulation model to access the userinteraction data received at step 222 to identify recent activity thatthe user engaged in (e.g., the user may be requesting assistance with arecent activity) and/or that has been identified as a frequentlyconducted activity (e.g., check account balance, or the like) based onaggregated user interaction data for a plurality of customers.Additionally or alternatively, the virtual assistant host platform 103may use the IVR simulation model to access frequently asked questions,or the like that may be aggregated based on virtual assistant sessionsbetween the virtual assistant host platform 103 and a plurality ofmobile devices 102 each corresponding to a different customer. Using theIVR simulation as described above, the virtual assistant host platform103 may predict requests that the user may be likely to make, and maygenerate hotkey information corresponding to these predicted requests.For example, the virtual assistant host platform 103 may identify thatthe user recently attempted to cash a check at the enterprise computingdevice 104, but the transaction failed. In this example, the virtualassistant host platform 103 may determine that the user is likelyplanning to request an explanation or assistance corresponding to thefailed transaction, and accordingly, the virtual assistant host platform103 may generate hotkey information indicating “Please select 1 forassistance with your failed check deposit on Jun. 23, 2020.” Similarly,the virtual assistant host platform 103 may generate hotkey informationindicating a number to select on the mobile device 102 to requestinformation, process an event, or the like (e.g., the virtual assistanthost platform 103 may link one request or event to each number displayedon the mobile device 102 (e.g., 0-9)). For example, the virtualassistant host platform 103 may generate hotkey information indicating anumber to select on the mobile device 102 to identify an accountbalance, a transaction status, failed transaction information, creditscore information, credit card information, charge/payment information,account information, mortgage information, outage information, or thelike. Additionally or alternatively, the virtual assistant host platform103 may generate hotkey information indicating a number to select on themobile device 102 to process or otherwise execute a transaction, fundtransfer, or the like. For example, the virtual assistant host platform103 may generate hotkey information that may be used to indicate “Pleaseselect [0-9] to perform [task, request, process event, or the like].”

In one or more instances, in the virtual assistant host platform 103 maygenerate different hotkey information for the user during each virtualassistant session (e.g., based on updated and/or newly received userinteraction information). For example, the virtual assistant hostplatform 103 may generate first hotkey information for the user during afirst virtual assistant session based on a first predicted user intentidentified from first user interaction information, and may (e.g.,several days, weeks, months, or the like) later generate second hotkeyinformation for the user during a second virtual assistant session basedon a second predicted user intent identified from second userinteraction information. Similarly, the virtual assistant host platform103 may generate different hotkey information for different customers(e.g., based on user interaction information corresponding to eachcustomer). For example, the virtual assistant host platform 103 maygenerate first hotkey information for a first user during a firstvirtual assistant session based on a predicted user intent for the firstuser identified from user interaction information corresponding to thefirst user, and may generate second hotkey information for a second userduring a second virtual assistant session based on a predicted userintent for the second user identified from user interaction informationcorresponding to the second user. In doing so, the virtual assistanthost platform 103 may generate dynamic and customized hotkey informationspecific to individual customers at a given time. Additionally, thevirtual assistant host platform 103 may generate one or more commandsdirecting the mobile device 102 to convert the hotkey information to ahotkey audio output, and to output the hotkey audio output.

Referring to FIG. 2F, at step 226, the virtual assistant host platform103 may send the hotkey information and/or one or more commandsdirecting the mobile device 102 to convert the hotkey information to thehotkey audio output, and to output the hotkey audio output to the mobiledevice 102. For example, the virtual assistant host platform 103 maysend the hotkey information and/or one or more commands directing themobile device 102 to convert the hotkey information to the hotkey audiooutput, and to output the hotkey audio output via the communicationinterface 113 and while the first wireless data connection isestablished.

At step 227, the mobile device 102 may receive the hotkey informationand/or one or more commands directing the mobile device 102 to convertthe hotkey information to the hotkey audio output, and to output thehotkey audio output. For example, the mobile device 102 may receive thehotkey information and/or one or more commands directing the mobiledevice 102 to convert the hotkey information to the hotkey audio output,and to output the hotkey audio output while the first wireless dataconnection is established.

At step 228, the mobile device 102 may generate an audio hotkey output,and may output the audio hotkey output. For example, the mobile device102 may generate and output the audio hotkey output based on or inresponse to the hotkey information and/or the one or more commandsdirecting the mobile device 102 to convert the hotkey information to thehotkey audio output, and to output the hotkey audio output. For example,the mobile device 102 may output “Please select 1 for your accountbalance, please select 2 for more information about your failed checkdeposit on Jun. 23, 2020 . . . ” or the like.

At step 229, the mobile device 102 may receive a hotkey input. Forexample, the mobile device 102 may receive a user input corresponding toa selection of one of the numbers displayed on the mobile device 102. Insome instances, the mobile device 102 may receive a user input selectinga particular inquiry to be made, event to be processed, or the like. Inother instances, the mobile device 102 may receive a user inputindicating that the hotkey audio output does not correspond to theactual intent of the user, and requesting to speak with a liverepresentative. In these instances, the mobile device 102 may contact acall center and cause a voice call session to be established between themobile device 102 and a computing device operated by an employee of theenterprise organization (e.g., a customer service representative at acall center for a financial institution). In operating in this manner,the mobile device 102 and the virtual assistant host platform 103 mayreduce load on representatives and/or computing resources at the callcenter by automatically handling a large percentage of requests throughthe hotkey selection process. Similarly, this may reduce customer delays(e.g., the user does not need to wait for a live representative, or, ifhe or she does need a live representative, due to the reduced load, waittimes may be reduced or eliminated).

At step 230, the mobile device 102 may send hotkey input information(e.g., based on the hotkey input received at step 229) to the virtualassistant host platform 103. For example, the mobile device 102 may sendthe hotkey input information to the virtual assistant host platform 103while the first wireless data connection is established.

At step 231, the virtual assistant host platform 103 may receive thehotkey input information sent at step 230. For example, the virtualassistant host platform 103 may receive the hotkey input information viathe communication interface 113 and while the first wireless dataconnection is established.

In some instances, the virtual assistant host platform 103 may identifywhether or not it has locally stored information or is otherwiseconfigured to process the hotkey input information without assistancefrom the event processing system 105. If the virtual assistant hostplatform 103 is configured to process the hotkey input information usinglocal resources, the virtual assistant host platform 103 may proceed tostep 237. If the virtual assistant host platform 103 is not configuredto satisfy the intent using local resources, the virtual assistant hostplatform 103 may proceed to step 232.

Referring to FIG. 2G, at step 232, the virtual assistant host platform103 may send one or more event processing commands to the eventprocessing system 105 (e.g., commands to process a request, event,transaction, or the like based on the hotkey input information). Forexample, the virtual assistant host platform 103 may send the one ormore event processing commands to the event processing system 105 viathe communication interface 113 and while the second wireless dataconnection is established. Actions performed at step 232 may be similarto those described above with regard to step 209.

At step 233, the event processing system 105 may receive the one or moreevent processing commands sent at step 232. For example, the eventprocessing system 105 may receive the one or more event processingcommands while the second wireless data connection is established.Actions performed at step 233 may be similar to those described abovewith regard to step 210.

At step 234, the event processing system 105 may process an event,provide a response to an inquiry, or the like based on or in response tothe one or more event processing commands received at step 233. Forexample, the event processing system 105 may identify an accountbalance, a transaction status, failed transaction information, creditscore information, credit card information, charge/payment information,account information, mortgage information, outage information, or thelike. Additionally or alternatively, the event processing system 105 mayprocess or otherwise execute a transaction, fund transfer, or the like.Actions performed at step 234 may be similar to those described abovewith regard to step 211.

At step 235, the event processing system 105 may generate and send anevent processing notification based on the event and/or inquiryprocessed at step 234. For example, the event processing system 105 maygenerate a notification indicating an account balance, a transactionstatus, failed transaction information, credit score information, creditcard information, charge/payment information, account information,mortgage information, outage information, or the like. Additionally oralternatively, the event processing system 105 may generate anotification indicating that a transaction, fund transfer, or the likewas executed. In some instances, the event processing system 105 maysend the event processing notification to the virtual assistant hostplatform 103 while the second wireless data connection is established.Actions performed at step 235 may be similar to those described above atstep 212.

At step 236, the virtual assistant host platform 103 may receive theevent processing notification sent at step 235. For example, the virtualassistant host platform 103 may receive the event processingnotification via the communication interface 113 and while the secondwireless data connection is established. Actions performed at step 236may be similar to those described above with regard to step 213.

At step 237, the virtual assistant host platform 103 may generate andsend a hotkey response message based on the event processingnotification received at step 236. For example, the virtual assistanthost platform 103 may generate the response message based on theinformation included in the event processing notification. In someinstances, in addition to the response message, the virtual assistanthost platform 103 may generate one or more commands directing the mobiledevice 102 to convert the response message from text to audio, and tooutput the converted audio response message.

In some instances, the virtual assistant host platform 103 may send thehotkey response message and/or the one or more commands directing themobile device 102 to convert the hotkey response message from text toaudio, and to output the converted hotkey audio response message to themobile device 102. For example, the virtual assistant host platform 103may send the hotkey response message and/or the one or more commandsdirecting the mobile device 102 to convert the hotkey response messagefrom text to audio, and to output the converted hotkey audio responsemessage via the communication interface 113 and while the first wirelessdata connection is established. Actions performed at step 237 may besimilar to those described above at steps 214-215.

At step 238, the mobile device 102 may receive the hotkey responsemessage and/or the one or more commands directing the mobile device 102to convert the hotkey response message from text to audio, and to outputthe converted hotkey audio response message to the mobile device 102sent at step 237. For example, the mobile device 102 may receive thehotkey response message and/or the one or more commands directing themobile device 102 to convert the hotkey response message from text toaudio, and to output the converted hotkey audio response message via thecommunication interface 113 and while the first wireless data connectionis established. Actions performed at step 238 may be similar to thosedescribed above at step 216.

Referring to FIG. 2H, at step 239, the mobile device 102 may convert thehotkey response message to a hotkey audio response output. For example,the mobile device 102 may use one or more text to speech techniques toconvert the hotkey response message (e.g., which may be in text form) toan audio response output. In some instances, the mobile device 102 mayconvert the hotkey response message to a hotkey audio response outputbased on or in response to the one or more commands directing the mobiledevice 102 to convert the hotkey response message from text to audio,and to output the converted hotkey audio response message. Actionsperformed at step 239 may be similar to those described above withregard to step 217.

At step 240, the mobile device 102 may output the hotkey audio responseoutput generated at step 239. For example, the mobile device 102 mayoutput the hotkey audio response output based on or in response to theone or more commands directing the mobile device 102 to convert thehotkey response message from text to audio, and to output the convertedhotkey audio response message. For example, the mobile device 102 maycause an audio output of an account balance, a transaction status,failed transaction information, credit score information, credit cardinformation, charge/payment information, account information, mortgageinformation, outage information, a transaction status, or the like as aresponse to the hotkey input information sent at step 230. In someinstances, the mobile device 102 may receive feedback corresponding tothe hotkey audio response output (e.g., did it satisfy the user intent,or the like), and may send the feedback to the virtual assistant hostplatform 103, which may update the IVR simulation model accordingly.Actions performed at step 240 may be similar to those described abovewith regard to step 218.

FIG. 3 depicts an illustrative method for implementing machine learningto enable IVR simulation in accordance with one or more exampleembodiments. Referring to FIG. 3, at step 305, a computing platformhaving at least one processor, a communication interface, and memory mayinitiate a virtual assistance session. At step 310, the computingplatform may receive an assistance message from a mobile devicerequesting virtual assistance. At step 315, the computing platform mayidentify an intent of the assistance message. At step 320, the computingplatform may identify whether event processing is requested. If not, thecomputing platform may proceed to step 335. If event processing isrequested, the computing platform may proceed to step 325.

At step 325, the computing platform may send an event processing requestto an event processing system. At step 330, the computing platform mayreceive an event processing notification indicating a status or otherinformation corresponding to the processed event. At step 335, thecomputing platform may generate a response message that satisfies theidentified intent of the assistance message. At step 340, the computingplatform may send the response message to the mobile device.

FIG. 4 depicts an illustrative method for implementing machine learningto enable IVR simulation in accordance with one or more exampleembodiments. Referring to FIG. 4, at step 405, a computing platformhaving at least one processor, a communication interface, and memory mayreceive user interaction data corresponding to interactions between acustomer and one or more enterprise computing devices. At step 410, thecomputing platform may initiate a virtual assistance session with amobile device. At step 415, the computing platform may identify a usercorresponding to the mobile device. At step 420, the computing platformmay generate and send hotkey information to the mobile device. At step425, the computing platform may receive hotkey input information fromthe mobile device. At step 430, the computing platform may identifywhether event processing was requested by the mobile device. If eventprocessing was not requested, the computing platform may proceed to step445. If event processing was requested, the computing platform mayproceed to step 435.

At step 435, the computing platform may send an event processing requestto an event processing system. At step 440, the computing platform mayreceive an event processing notification indicating a status and/orother information corresponding to the processed event. At step 445, thecomputing platform may generate and send a response message to themobile device indicating a response to the hotkey input information.

One or more aspects of the disclosure may be embodied in computer-usabledata or computer-executable instructions, such as in one or more programmodules, executed by one or more computers or other devices to performthe operations described herein. Generally, program modules includeroutines, programs, objects, components, data structures, and the likethat perform particular tasks or implement particular abstract datatypes when executed by one or more processors in a computer or otherdata processing device. The computer-executable instructions may bestored as computer-readable instructions on a computer-readable mediumsuch as a hard disk, optical disk, removable storage media, solid-statememory, RAM, and the like. The functionality of the program modules maybe combined or distributed as desired in various embodiments. Inaddition, the functionality may be embodied in whole or in part infirmware or hardware equivalents, such as integrated circuits,application-specific integrated circuits (ASICs), field programmablegate arrays (FPGA), and the like. Particular data structures may be usedto more effectively implement one or more aspects of the disclosure, andsuch data structures are contemplated to be within the scope of computerexecutable instructions and computer-usable data described herein.

Various aspects described herein may be embodied as a method, anapparatus, or as one or more computer-readable media storingcomputer-executable instructions. Accordingly, those aspects may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, an entirely firmware embodiment, or an embodiment combiningsoftware, hardware, and firmware aspects in any combination. Inaddition, various signals representing data or events as describedherein may be transferred between a source and a destination in the formof light or electromagnetic waves traveling through signal-conductingmedia such as metal wires, optical fibers, or wireless transmissionmedia (e.g., air or space). In general, the one or morecomputer-readable media may be and/or include one or more non-transitorycomputer-readable media.

As described herein, the various methods and acts may be operativeacross one or more computing servers and one or more networks. Thefunctionality may be distributed in any manner, or may be located in asingle computing device (e.g., a server, a client computer, and thelike). For example, in alternative embodiments, one or more of thecomputing platforms discussed above may be combined into a singlecomputing platform, and the various functions of each computing platformmay be performed by the single computing platform. In such arrangements,any and/or all of the above-discussed communications between computingplatforms may correspond to data being accessed, moved, modified,updated, and/or otherwise used by the single computing platform.Additionally or alternatively, one or more of the computing platformsdiscussed above may be implemented in one or more virtual machines thatare provided by one or more physical computing devices. In sucharrangements, the various functions of each computing platform may beperformed by the one or more virtual machines, and any and/or all of theabove-discussed communications between computing platforms maycorrespond to data being accessed, moved, modified, updated, and/orotherwise used by the one or more virtual machines.

Aspects of the disclosure have been described in terms of illustrativeembodiments thereof. Numerous other embodiments, modifications, andvariations within the scope and spirit of the appended claims will occurto persons of ordinary skill in the art from a review of thisdisclosure. For example, one or more of the steps depicted in theillustrative figures may be performed in other than the recited order,and one or more depicted steps may be optional in accordance withaspects of the disclosure.

What is claimed is:
 1. A computing platform, comprising: at least oneprocessor; a communication interface communicatively coupled to the atleast one processor; and memory storing computer-readable instructionsthat, when executed by the at least one processor, cause the computingplatform to: establish a virtual assistant session with a mobile bankingapplication executing on a mobile device, wherein establishing thevirtual assistant session with the mobile banking application executingon the mobile device comprises authenticating at least oneauthentication credential associated with an online banking account;receive an assistance message from the mobile device requestingassistance; identify, using a machine learning model, an intent of theassistance message; generate a response message based on the intent ofthe assistance message; and send the response message and one or morecommands directing the mobile device to output an audio response filebased on the response message to the mobile device, wherein sending theresponse message and the one or more commands directing the mobiledevice to output the audio response file based on the response messagecauses the mobile device to convert the response message into the audioresponse file and output the audio response file.
 2. The computingplatform of claim 1, wherein authenticating the at least oneauthentication credential associated with the online banking accountcomprises authenticating one or more of: a user name, a password,biometric information, or a voice input.
 3. The computing platform ofclaim 1, wherein the memory stores additional computer-readableinstructions that, when executed by the at least one processor, furthercause the computing platform to: prior to identifying the intent, trainthe machine learning model based on a plurality of recorded interactivevoice response (IVR) sessions, wherein the plurality of recordedinteractive voice response sessions correspond to one or more of: phonesessions or virtual IVR sessions with one or more online bankingcustomers.
 4. The computing platform of claim 1, wherein identifying theintent comprises identifying one or more of: a balance inquiry request,a transaction status request, a request for information corresponding toa failed transaction, a credit score inquiry, credit card information,charge/payment information, a request for account information, amortgage request, a request to execute a transaction, or a request foroutage information.
 5. The computing platform of claim 1, whereingenerating the response message based on the intent of the assistancemessage comprises: sending one or more commands directing an eventprocessing system to process an event based on the intent of theassistance message, wherein sending the one or more commands directingthe event processing system to process the event based on the intent ofthe assistance message cause the event processing system to process theevent; receiving, from the event processing system, an event processingnotification indicating that the event was processed; and generating,based on the event processing notification indicating that the event wasprocessed, the assistance message.
 6. The computing platform of claim 1,wherein identifying the intent of the assistance message comprisesidentifying the intent of the assistance message based at least in parton information from the mobile device.
 7. The computing platform ofclaim 1, wherein the virtual assistant session corresponds to a datachannel between the mobile device and an artificial intelligence enginehosted by the computing platform.
 8. A method comprising: at a computingplatform comprising at least one processor, a communication interface,and memory: establishing a virtual assistant session with a mobilebanking application executing on a mobile device, wherein establishingthe virtual assistant session with the mobile banking applicationexecuting on the mobile device comprises authenticating at least oneauthentication credential associated with an online banking account;receiving an assistance message from the mobile device requestingassistance; identifying, using a machine learning model, an intent ofthe assistance message; generating a response message based on theintent of the assistance message; and sending the response message andone or more commands directing the mobile device to output an audioresponse file based on the response message to the mobile device,wherein sending the response message and the one or more commandsdirecting the mobile device to output the audio response file based onthe response message causes the mobile device to convert the responsemessage into the audio response file and output the audio response file.9. The method of claim 8, wherein authenticating the at least oneauthentication credential associated with the online banking accountcomprises authenticating one or more of: a user name, a password,biometric information, or a voice input.
 10. The method of claim 8,further comprising: prior to identifying the intent, training themachine learning model based on a plurality of recorded interactivevoice response (IVR) sessions, wherein the plurality of recordedinteractive voice response sessions correspond to one or more of: phonesessions or virtual IVR sessions with one or more online bankingcustomers.
 11. The method of claim 8, wherein identifying the intentcomprises identifying one or more of: a balance inquiry request, atransaction status request, a request for information corresponding to afailed transaction, a credit score inquiry, credit card information,charge/payment information, a request for account information, amortgage request, a request to execute a transaction, or a request foroutage information.
 12. The method of claim 8, wherein generating theresponse message based on the intent of the assistance messagecomprises: sending one or more commands directing an event processingsystem to process an event based on the intent of the assistancemessage, wherein sending the one or more commands directing the eventprocessing system to process the event based on the intent of theassistance message cause the event processing system to process theevent; receiving, from the event processing system, an event processingnotification indicating that the event was processed; and generating,based on the event processing notification indicating that the event wasprocessed, the assistance message.
 13. The method of claim 8, whereinidentifying the intent of the assistance message comprises identifyingthe intent of the assistance message based at least in part oninformation from the mobile device.
 14. One or more non-transitorycomputer-readable media storing instructions that, when executed by acomputing platform comprising at least one processor, a communicationinterface, and memory, cause the computing platform to: establish avirtual assistant session with a mobile banking application executing ona mobile device, wherein establishing the virtual assistant session withthe mobile banking application executing on the mobile device comprisesauthenticating at least one authentication credential associated with anonline banking account; receive an assistance message from the mobiledevice requesting assistance; identify, using a machine learning model,an intent of the assistance message; generate a response message basedon the intent of the assistance message; and send the response messageand one or more commands directing the mobile device to output an audioresponse file based on the response message to the mobile device,wherein sending the response message and the one or more commandsdirecting the mobile device to output the audio response file based onthe response message causes the mobile device to convert the responsemessage into the audio response file and output the audio response file.15. The one or more non-transitory computer-readable media of claim 14,wherein authenticating the at least one authentication credentialassociated with the online banking account comprises authenticating oneor more of: a user name, a password, biometric information, or a voiceinput.
 16. The one or more non-transitory computer-readable media ofclaim 14, wherein the memory stores additional computer-readableinstructions that, when executed by the at least one processor, furthercause the computing platform to: prior to identifying the intent, trainthe machine learning model based on a plurality of recorded interactivevoice response (IVR) sessions, wherein the plurality of recordedinteractive voice response sessions correspond to one or more of: phonesessions or virtual IVR sessions with one or more online bankingcustomers.
 17. The one or more non-transitory computer-readable media ofclaim 14, wherein identifying the intent comprises identifying one ormore of: a balance inquiry request, a transaction status request, arequest for information corresponding to a failed transaction, a creditscore inquiry, credit card information, charge/payment information, arequest for account information, a mortgage request, a request toexecute a transaction, or a request for outage information.
 18. The oneor more non-transitory computer-readable media of claim 14, whereingenerating the response message based on the intent of the assistancemessage comprises: sending one or more commands directing an eventprocessing system to process an event based on the intent of theassistance message, wherein sending the one or more commands directingthe event processing system to process the event based on the intent ofthe assistance message cause the event processing system to process theevent; receiving, from the event processing system, an event processingnotification indicating that the event was processed; and generating,based on the event processing notification indicating that the event wasprocessed, the assistance message.
 19. The one or more non-transitorycomputer-readable media of claim 14, wherein identifying the intent ofthe assistance message comprises identifying the intent of theassistance message based at least in part on information from the mobiledevice.
 20. The one or more non-transitory computer-readable media ofclaim 14, wherein the virtual assistant session corresponds to a datachannel between the mobile device and an artificial intelligence enginehosted by the computing platform.